电讯技术2026，Vol.66Issue(3)：343-349,7.DOI:10.20079/j.issn.1001-893x.240829001
基于Sinc函数和径向基神经网络的非线性干扰对消方法
Nonlinear Interference Cancellation Method Based on Sinc Function and Radial Basis Function Neural Network
摘要
Abstract
In view of the increasingly serious problem of nonlinear adjacent channel co-location interference caused by dense high-power channel layout in civil aviation air traffic control,a combined analog-digital interference cancellation method based on cardinal sine(Sinc)function and radial basis function neural network(RBFNN)is proposed.Firstly,through Sinc function and gradient optimization algorithm,a nonlinear simulation cancellation model is established to eliminate multipath influence and to a certain extent eliminate co-location interference.Then,by fusing the detection features of adjacent channel signals and interference residual features through RBFNN,a nonlinear digital cancellation model is established to further cancel residual interference.Experiments have shown that this method can quickly eliminate nonlinear co-location interference while effectively preserving the useful signal in the received signal.Under the condition of 60 dB interference-to-signal ratio,the interference cancellation ratio can reach 99.7 dB,which is at least 24 dB higher than that of the existing methods;the loss degree of useful signal is only 11.9 dB,which is at least 18 dB lower than that of the existing method;the interference cancellation time is only 70 μs,which is at least 35 μs shorter than that of existing methods.关键词
空中交通管理/非线性干扰/共址干扰/干扰对消/径向基神经网络(RBFNN)Key words
air traffic control/nonlinear interference/co-location interference/interference cancellation/radial basis function neural network(RBFNN)分类
信息技术与安全科学引用本文复制引用
姚元飞,邱吉刚,张小舟,蔡方凯,吴建光..基于Sinc函数和径向基神经网络的非线性干扰对消方法[J].电讯技术,2026,66(3):343-349,7.基金项目
四川省科技成果转移转化示范项目(2024ZHCG0046) （2024ZHCG0046）
